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data
How data became an important resource
What data scientists do
How Udacity uses data
1. They don’t know what it’s saying
2. They ignore what it’s saying
2 reasons companies struggle with their big data
1. They don’t know what it’s saying
2. They ignore what it’s saying
2 reasons companies struggle with big data
Data analysts turn data into actionable business insights
Engineering
BusinessDesign
Data Analysts
Product
data request
build something (model, chart, report,
dashboard, test)
How Udacity uses Data
https://www.dropbox.com/s/uf7eoyxj5m0dofn/Screenshot%202016-10-13%2015.31.18.png?dl=0Course Recommendations
A/B Testing
Counting
4 reasons why counting is hard1. Counting requires numerous, often arbitrary decisions2. Counting is easy to understand3. Counting is often high-stakes
http://daynebatten.com/2016/06/counting-hard-data-science/
WSJ, Sep 2016
Survival Analysis
Kaplan–Meier estimator
3. Data VisualizationWhy does it matter?
Graphic design for scientistsKaren Cheng & Marco RolandiNature Nanotechnology 10, 1084 (2015)
Small multiples
Dashboard Design
